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Randomization as Regularization: A Degrees of Freedom Explanation for Random Forest Success
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Randomization as Regularization: A Degrees of Freedom Explanation for Random Forest Success

L. Mentch
Siyu Zhou
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Papers citing "Randomization as Regularization: A Degrees of Freedom Explanation for Random Forest Success"

15 / 15 papers shown
Title
Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests
Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests
Brian Liu
Rahul Mazumder
137
1
0
20 Feb 2024
SR-PredictAO: Session-based Recommendation with High-Capability Predictor Add-On
SR-PredictAO: Session-based Recommendation with High-Capability Predictor Add-On
Ruida Wang
Raymond Chi-Wing Wong
Weile Tan
43
1
0
20 Sep 2023
Generalized equivalences between subsampling and ridge regularization
Generalized equivalences between subsampling and ridge regularization
Pratik V. Patil
Jin-Hong Du
91
5
0
29 May 2023
Model-Agnostic Confidence Intervals for Feature Importance: A Fast and Powerful Approach Using Minipatch Ensembles
Model-Agnostic Confidence Intervals for Feature Importance: A Fast and Powerful Approach Using Minipatch Ensembles
Luqin Gan
Lili Zheng
Genevera I. Allen
94
6
0
05 Jun 2022
Sequential Permutation Testing of Random Forest Variable Importance Measures
Sequential Permutation Testing of Random Forest Variable Importance Measures
Alexander Hapfelmeier
R. Hornung
Bernhard Haller
54
15
0
02 Jun 2022
Is interpolation benign for random forest regression?
Is interpolation benign for random forest regression?
Ludovic Arnould
Claire Boyer
Erwan Scornet
78
6
0
08 Feb 2022
Hierarchical Shrinkage: improving the accuracy and interpretability of tree-based methods
Hierarchical Shrinkage: improving the accuracy and interpretability of tree-based methods
Abhineet Agarwal
Yan Shuo Tan
Omer Ronen
Chandan Singh
Bin Yu
90
27
0
02 Feb 2022
Local Adaptivity of Gradient Boosting in Histogram Transform Ensemble Learning
Local Adaptivity of Gradient Boosting in Histogram Transform Ensemble Learning
H. Hang
30
0
0
05 Dec 2021
Muddling Label Regularization: Deep Learning for Tabular Datasets
Muddling Label Regularization: Deep Learning for Tabular Datasets
Karim Lounici
Katia Méziani
Benjamin Riu
85
6
0
08 Jun 2021
Trees, Forests, Chickens, and Eggs: When and Why to Prune Trees in a Random Forest
Trees, Forests, Chickens, and Eggs: When and Why to Prune Trees in a Random Forest
Siyu Zhou
L. Mentch
55
22
0
30 Mar 2021
An Embedded Model Estimator for Non-Stationary Random Functions using Multiple Secondary Variables
An Embedded Model Estimator for Non-Stationary Random Functions using Multiple Secondary Variables
C. Daly
21
5
0
09 Nov 2020
To Bag is to Prune
To Bag is to Prune
Philippe Goulet Coulombe
UQCV
54
9
0
17 Aug 2020
Macroeconomic Data Transformations Matter
Macroeconomic Data Transformations Matter
Philippe Goulet Coulombe
Maxime Leroux
D. Stevanovic
Stéphane Surprenant
63
22
0
04 Aug 2020
Getting Better from Worse: Augmented Bagging and a Cautionary Tale of Variable Importance
Getting Better from Worse: Augmented Bagging and a Cautionary Tale of Variable Importance
L. Mentch
Siyu Zhou
102
14
0
07 Mar 2020
Asymptotic Distributions and Rates of Convergence for Random Forests via Generalized U-statistics
Asymptotic Distributions and Rates of Convergence for Random Forests via Generalized U-statistics
Weiguang Peng
T. Coleman
L. Mentch
95
41
0
25 May 2019